Comparative analysis of trajectory control strategies for redundant cooperative space robot systems

Abstract

In many space exploration missions, where precise trajectory control is essential for successful operations, space robotics plays a critical role. This paper uses bond graph modeling to describe the dynamics of the system and to efficiently apply control schemes. This modeling method provides a strong framework for examining the behaviour and interactions of systems. Although bond graph modeling and Proportional-Integral-Derivative (PID) control are frequently combined, PID controllers frequently perform less than optimally in complicated or nonlinear systems. The controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to get over this restriction. GA simulates the process of natural selection and evolution while, PSO a population-based optimization method, imitates the behaviour of a swarm. The goal of both algorithms is to determine the PID parameters in order to reduce trajectory errors and improve efficiency. This study presents an enhanced capability for redundant space robots to manage their trajectory during contacts with free-floating objects by merging PID with PSO and GA respectively.

Keywords

space robot control PID bond graph robot trajectory

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References

She

. An extra degree-of-freedom model for combined spacecraft attitude control with unilateral contact constraint. Acta Astronaut 2019; 1(165): 54–67.

Patolia

Pathak

Jain

. Docking operation by two DOF dual arm planar cooperative space robot. 4th National Conference on Machines and Mechanisms 2009; 17: 206–213.

Moghaddam

Chhabra

. On the guidance, navigation and control of in-orbit space robotic missions: a survey and prospective vision. Acta Astronaut 2021; 1(184): 70–100.

Dongming

Guanghui

Yuanjie

, et al. Impedance control of multi-arm space robot for the capture of non-cooperative targets. J Syst Eng Electron 2020; 31(5): 1051–1061.

Yan

, et al. Virtual-base modeling and coordinated control of a dual-arm space robot for target capturing and manipulation. Multibody Syst Dyn 2019; 45(4): 431–455.

Dalla

Pathak

. Obstacle avoiding reconfigurable high dof space robot manipulator. In: The international conference on Inte- grated modeling and analysis in applied control and automation (IMAACA), September 21–23, Italy.

Dixit

Fallah

Montanaro

, et al. Trajectory planning and tracking for autonomous overtaking: state-of-the-art and future prospects. Annu Rev Control 2018; 1(45): 76–86.

Dalla

Pathak

. Trajectory control of curve Con- strained hyper-redundant space manipulator. In: Proceedings of the 14th IFToMM World Congress Nov 4, IEEE, 2015, pp. 367–374.

Zhang

Yan

Zhang

, et al. Collision avoidance in fixed-wing UAV formation flight based on a consensus control algorithm. IEEE Access 2018; 6: 43672–43682.

10.

Henshaw

Glassner

Naasz

, et al. Grappling spacecraft. Annu Rev Control Robot Auton Syst 2022; 5: 137–159.

11.

Alattas

Patel

Sobh

. Evolutionary modular robotics: survey and analysis. J Intell Rob Syst 2019; 95: 815–828.

12.

Rybus

Wojtunik

Basmadji

. Optimal collision-free path planning of a free-floating space robot using spline-based trajectories. Acta Astronaut 2022; 190: 395–408.

13.

Jia

Meng

Huang

. Attitude control for tethered towing debris under actuators and dynamics uncertainty. Adv Space Res 2019; 64(6): 1286–1297.

14.

Xie

Inamori

, et al. Compensation of base disturbance using optimal trajectory planning of dual-manipulators in a space robot. Adv Space Res 2019; 63(3): 1147–1160.

15.

Samewoi

Azlan

Khan

, et al. Computed torque and velocity feedback control of cooperative manipulators handling a flexible beam. IJNeaM. 2020; 13: 17–34.

16.

Sahu

Balamurali

Mahanta

, et al. A heuristic comparison of optimization algorithms for the trajectory planning of a 4-axis SCARA robot manipulator. In: Computational Intelligence in Data Mining: Proceedings of the International Conference on CIDM 2017. Springer, 2019, pp. 569–582.

17.

Ahmadi

Fateh

. Task-space control of robots using an adaptive Taylor series uncertainty estimator. Int J Control 2019; 92(9): 2159–2169.

18.

Papadopoulos

Aghili

, et al. Robotic manipulation and capture in space: a survey. Frontiers in Robotics and AI. 2021; 8: 228.

19.

Smith

Karayiannidis

Nalpantidis

, et al. Dual arm manipulation—A survey. Robot Autonom Syst 2012; 60(10): 1340–1353.

20.

Dalla

Pathak

. Reconfiguration of joint locked hyper-redundant space manipulator. In: Proceedings of the 2015 Conference on Advances in Robotics, IEEE, 2015, pp. 1–6.

21.

Dalla

Pathak

. Curve-constrained collision-free trajectory control of hyper-redundant planar space robot. Proc IME J Syst Control Eng 2017; 231(4): 282–298.

22.

Shah

Agashe

. Review of fractional PID controller. Mechatronics 2016; 38: 29–41.

23.

Arora

Bera

. Impedance control of three-dimensional hybrid manipulator. J Mech Sci Technol 2020; 34: 359–367.

24.

Kennedy

Eberhart

. Particle swarm optimization. In: Proceedings of IEEE ICNN'95-International Conference on Neural Networks, IEEE, 1995, pp. 1942–1948.

25.

Mitchell

. An introduction to genetic algorithms. MIT press, 1998.